Sustailient supplier selection using neutrosophic best–worst approach: a case study of additively manufactured trinkets

Abstract

PurposeThis research work has developed an integrated fuzzy Delphi and neutrosophic best–worst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.Design/methodology/approachAn integrated fuzzy Delphi method (FDM) and neutrosophic best–worst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.FindingsThe outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.Research limitations/implicationsThe applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.Originality/valueThis is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

Advancing Sustainable Decision Making in Additive Manufacturing: A Comprehensive Review of Multi-Criteria Decision Making Approaches

“…In a research work by Ambilkar et al, an integrated fuzzy Delphi and neutrosophic best-worst framework for selecting a sustailient (sustainable and resilient) supplier for an AM-enabled industry was developed [28]. Supplier selection plays an important role in an organization's productivity, profitability, and stakeholder relations [23].…”

An assessment framework to evaluate the critical success factors to Quality 4.0 transition in developing countries: a case experience of sustainable performance of Indian manufacturers

“…Fuzzy-Delphi has the capacity to capture inherent vagueness within data. Many researchers use this method across a wide range of subject areas; these include business resilience and sustainability (Kumar and Anbanandam, 2019; Torres Vergara et al ., 2023); Demand forecasting (Khan et al ., 2023a, b; Zhu et al ., 2023); inventory management (Khan et al ., 2023a, b; Saputra, 2023); supplier selection (Ambilkar et al ., 2023; Ebrahimi et al ., 2023); risk management (Jahanvand et al ., 2023; Tuni et al ., 2023); production planning and quality control (Rana et al ., 2023); supply chain optimization (Khan et al ., 2023a, b; Tseng et al ., 2022); new product introduction (Lianto, 2023); sustainability and environmental impact (Mukherjee and Pradeep, 2023) and resource allocation (Shao et al ., 2023). Fuzzy logic allows for the representation of uncertainty and vagueness in the data (Lin et al ., 2018; Zhang et al ., 2023).…”